Long-term demand forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. One of the primary tasks of an electric utility accurately predicts load demand requirements at all times, especially for long-term. Based on the outcome of such forecasts, utilities coordinate their resources to meet the forecasted demand using a least-co...

the hub location decision is a long term investment and any changes in it take considerable time and money. in real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. the ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. in the two-stage stochastic programm...

R policies are common in many sectors of retail distribution. Padmanabhan and Png (1997) showed that with demand uncertainty, a returns policy could improve manufacturer profitability under certain conditions. Wang (2004) showed that returns policies do not change manufacturer profitability when demand is certain and retailing is competitive. We show that returns policies do increase manufactur...

This paper presents a model of the introduction of a product line that consists of a high-end model and a low-end model, under conditions of demand uncertainty. The firm is a-priori uncertain about the demand for the product line, which can turn out to be either high or low. The firm learns of the actual demand conditions only after at least one product in the line has been introduced. We start...

This paper presents a novel approach to compute optimal machine, shop oor and shell space expansion times under uncertain customer demand. It considers multiple machine types and allows for positive lead times for each type. Demand is assumed to be nondecreasing in a \weak" sense. A polynomial time algorithm (FIFEX) is developed and shown to be eeective and eecient with an example from the Semi...

Despite the existence of several weather studies in the tourism literature, there remain some gaps in knowledge. Uncertainty about weather conditions persists despite the impressive improvements in modern forecasting techniques. This study is a first attempt to investigate how weather uncertainty affects tourism demand. The findings indicate that the impact of weather on tourism demand is likel...

In this work, we provide an overview of our previously published works on incorporating demand uncertainty in midterm planning of multisite supply chains. A stochastic programming based approach is described to model the planning process as it reacts to demand realizations unfolding over time. In the proposed bilevel-framework, the manufacturing decisions are modeled as ‘here-and-now’ decisions...

How does demand uncertainty affect entry into skill-based competition? I investigate this question in a market entry experiment with skill-based payoffs by systematically varying two key elements of the market environment: demand risk and expected market size. Results show that people’s reactions to demand risk depend on the market size: in small markets people enter more when demand is risky, ...

We study collusive pricing in duopoly with uncertain demand and exogenous capacity constraints. In this setting, collusion using only symmetric pricing can limit collusive pro…ts. We …nd that using asymmetric pricing in some demand states permits higher sustainable collusive pro…ts over the entire range of demand states. Consequently, we show joint pro…t maximizing collusion can include both sy...

A Bayesian variable selection procedure is used to control for uncertainty in the specification of a recreational demand model. In contrast to comparing models based on the likelihood values with unknown sampling properties (as in, e.g., Egan et al, 2009), we propose a model that draws on the Bayesian paradigm to integrate the variable selection process into the model and reflect the accompanyi...